Article ID: | iaor20084536 |
Country: | Brazil |
Volume: | 27 |
Issue: | 3 |
Start Page Number: | 407 |
End Page Number: | 426 |
Publication Date: | Sep 2007 |
Journal: | Pesquisa Operacional |
Authors: | Steiner M.T.A., Soma N.Y., Nievola J.C. |
Keywords: | neural networks |
Credit-risk evaluation is a very important management science problem in the financial analysis area. Neural Networks have received a lot of attention because of their universal approximation property. They have a high predictive accuracy rate, but how they reach their decisions is not easy to understand. In this paper, we present a real-life credit-risk data set and analyzed it using the NeuroRule extraction technique and the software WEKA. The results were considered very satisfactory, reaching more than 80% of accuracy in granting or denying credit on every simulation.